Sharing your work
Sharing your work
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Sharing your work

This book is 90% complete

Last updated on 2019-08-13

About the Book

This text covers a toolchain for creating data products with RStudio, Git, and Github. Through a single case study (the 2019 democratic presidential debates), we describe how to use Git (via the command line) to track changes to files, how to create beautifully formatted reproducible reports with Rmarkdown, and how to turn your data project into a website using Github pages.

You will walk away with a working data product (lots of code, data, and visualizations) a ton of resources, and a book for reproducing this process again!

About the Author

Martin Frigaard
Martin Frigaard

Table of Contents

  • Introduction: A toolchain for making data products
    • What you will learn
    • Why write a book for a toolchain?
    • Who this book is for
    • How we know this toolchain works
    • Where do we find data?
    • What tools will I need?
    • After reading this book, you should feel better about…
    • What this book covers
    • What this book doesn’t cover
    • How this book is structured
    • What you’ll walk away with
  • Part 1: ‘Good enough’ data skills
    • Why ‘good enough’?
    • How to share your work
    • ‘Good enough’ communication
    • Get ‘good enough,’ then go for more if you need it
  • Part 2: “Have a workflow.”
    • Principle 1: Use open-source software
    • Principle 2: Write code
    • Principle 3: Document everything in plain text
    • Rmarkdown
    • Additional reasons for using R & RStudio
  • Part 3: Setting up your data science process
    • Example: FiveThirtyEight’s 2019 Presidential debate project
    • The Command line: Unix and Windows
    • Good enough command-line tools
    • Command line recap
  • Part 4: Keep track of changes with version control
    • Tracing our steps
    • Git
    • Setting up Git
  • Part 5: RStudio.Cloud
    • What have we done so far?
    • Recap on RStudio panes
    • Where should we write code?
    • Rmarkdown
    • Documenting our projects
    • Import
    • Document changes with Git
    • Wrangle
    • Visualize
    • Knitting RMarkdown files
  • Part 6: Putting your project on Github
    • What we’ve done
    • Sharing our work with Github pages
    • Conclusion
  • Appendix
    • Introduction: A toolchain for making data products
    • Chapter 1
    • Chapter 2
    • Chapter 3
    • Chapter 4
    • Chapter 5
    • Chapter 6

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